Carbamazepine (CBZ), one of the most used pharmaceuticals worldwide and a Contaminant of Emerging Concern, represents a potential risk for the environment and human health. Wastewater treatment plants (WWTPs) are a significant source of CBZ to the environment, polluting the whole water cycle. In this review, the CBZ presence and fate in the urban water cycle are addressed, with a focus on adsorption as a possible solution for its removal. Specifically, the scientific literature on CBZ removal by activated carbon and its possible substitute Biochar, is comprehensively scanned and summed up, in view of increasing the circularity in water treatments. CBZ adsorption onto activated carbon and biochar is analyzed considering several aspects, such as physicochemical characteristics of the adsorbents, operational conditions of the adsorption processes and adsorption kinetics and isotherms models. WWTPs usually show almost no removal of CBZ (even negative), whereas removal is witnessed in drinking water treatment plants through advanced treatments (even >90%). Among these, adsorption is considered one of the preferable methods, being economical and easier to operate. Adsorption capacity of CBZ is influenced by the characteristics of the adsorbent precursors, pyrolysis temperature and modification or activation processes. Among operational conditions, pH shows low influence on the process, as CBZ has no charge in most pH ranges. Differently, increasing temperature and rotational speed favor the adsorption of CBZ. The presence of other micro-contaminants and organic matter decreases the CBZ adsorption due to competition effects. These results, however, concern mainly laboratory-scale studies, hence, full-scale investigations are recommended to take into account the complexity of the real conditions.

This paper critically discusses the results of an experimental activity aimed at investigating the possibilities of μ-Raman analysis for routine monitoring of microplastics in drinking water in view of the application of the guidelines proposed by the European Union. Automatization in the water analysis reduces the required time and influence of the operator on the results. It is of utmost importance in the context of routine monitoring for the quality assessment. Automatized protocols selected from the state-of-the-art were implemented in a real monitoring campaign on a drinking water treatment plant from central Italy treating surface water. Technical limits were found in the performance of the automated image analysis algorithm and the motorized stage precision. Such limits might increase the lowest limit automatically analyzable by μ-Raman from 1 μm to 5 μm, whereas the assessment of MPs > 20 μm was not impaired. Regarding results reporting, it was highlighted the need of standardization in polymers grouping in major clusters. Regardless, the automation in the size range 20-500 μm was shown to be satisfactory and upgradable by few software adjustments. The overall analysis time was calculated to be about 4-5 h. The results also showed a MPs scarce contamination (<2MPs/L), coherently with the findings of previous studies.

Quality Assurance and -control (QA/QC) tools are essential to evaluate the reliability of data on nano- and microplastic particles measured in the human body for use in risk assessment. Currently, no such criteria exist for human samples. To support human health risk assessment related to internal exposure to these particles, we developed a QA/QC screening protocol with fourteen criteria across three categories: sampling methods, particle characterization, and contamination mitigation. We applied this tool to evaluate 130 datasets from 99 studies reporting measurements of microplastics in human organs, tissues, and bodily fluids. None of the studies nor datasets met all essential QA/QC criteria, indicating their current value lies primarily in pioneering exploratory research. Common gaps were found in sample representativeness, the use of positive controls, and documentation of blank procedures. Data were also sparse for organs critical to toxicokinetic processes and physiologically-based kinetic modelling, highlighting a significant knowledge gap. Even in studies with relatively strong QA/QC performance, some findings warrant careful evaluation of biological plausibility. We recommend that future studies not only improve QA/QC practices but also explicitly reflect on the plausibility of their results to avoid misinterpretation and miscommunication.

Urban rivers represent a highly vulnerable environment due to the intense anthropogenic pressures and the restricted self‐depuration capacity. The current monitoring programs often lack to provide a full knowledge of all contaminant sources and processes governing their behaviour due to the complexity and variability of the conditions in urban water bodies and the increasing occurrence of new pollutants such as the Contaminants of Emerging concern (CECs). This called for an increasing regulatory attention and the need to carry out the revision of the Water Framework Directive (WFD), as it is currently ongoing. This study proposes an integrated new approach for urban water quality assessment, which combines traditional parameters, emerging contaminants, (i.e. CECs and Microplastics-MPs), isotopic tracing and modelling, with the aim of improving source discrimination and advancing the understanding of contaminant dynamics in heavily modified urban rivers. The new approach was tested on a selected stretch of the Tiber river, within the city of Rome. Data of pollutant concentrations, measured along the water body close by the point source releases, were combined with the hydraulic information through a mass‐balance approach with the aim to quantify contributions of different processes. The stable isotope ratios were evaluated as tracers for identifying contaminant origins and potential transformation processes, representing an innovative application in the context of urban river monitoring. Additionally, the Qual2K model was employed to simulate water‐quality dynamics under varying hydrological and meteorological conditions, focusing on the behaviour of CECs.

Reliable exposure data is critical for determining the potential human health risks of microplastics. To date, however, exposure data are often difficult to compare and do not always meet quality criteria, limiting their suitability for risk assessment. This study aimed to provide a large-scale quality assessment (QA/QC) of studies on microplastics in the main human exposure routes: Air, Food, and Beverages. A hybrid method was used, in which an AI model (Gemini 1.5-pro) automatically extracted information from 950 studies, followed by logical score assignment using Python scripts. Building on earlier QA/QC screenings, each study was evaluated against 13 criteria and assigned a score of 2 (fully reliable), 1 (reliable with restrictions), or 0 (unreliable). AI performance was verified by human assessment in a statistically determined sample of studies (n= 87). The average total score across all datasets was 12 out of 26, with an average of 5.3 inadequate scores (zero scores) per study. The highest scoring studies achieved 20 points. The lowest scores were associated with criteria involving positive and negative controls, blank correction, and the representativeness of sampling and usage conditions. The results show that most current studies have significant shortcomings for application in risk assessment. In particular, data on Food and Air may not adequately represent actual human exposure. At the same time, this QA/QC analysis is the largest to date and the first to cover Air, Food, and Beverages simultaneously; it provides a valuable ranking of usable studies and makes large-scale risk assessment more feasible. The dataset can assist policymakers in selecting the most reliable data for health evaluations and underscores the need for standardization and improved analytical methods in future studies.